Dynamic playlist priority in a vehicle based upon user preferences and context

ABSTRACT

Systems, methods and computer program products that facilitate dynamic playlist priority in a vehicle based upon user preferences and context. According to an embodiment, a system comprises a processor that executes computer executable components stored in at least one memory, a compilation component that receives content in a vehicle, an assessment component that respectively classifies subsets of the content, a ranking component that ranks relevancy of the classified subsets of content based upon preferences and context of a user in the vehicle, a content playback component that plays the subsets of classified content based upon relevancy ranking, a prioritization component that dynamically prioritizes a first subset of the content based upon the context of the user or context of a sender of the first subset of content, wherein the first subset of content comprises extrinsic data, and an interrupt component that interrupts playback of the subsets of classified content based upon the dynamic prioritization.

TECHNICAL FIELD

Embodiments disclosed and claimed herein relate to techniques thatfacilitate dynamic playlist priority in a vehicle based upon userpreferences and context.

BACKGROUND

Users in vehicles have access to a wide variety of content throughentertainment and communication systems in vehicles or electronicdevices brought into vehicles. For example, users with access to asmartphone, smartwatch, tablet or other external user device that cansync with a vehicle's entertainment and communication systems can accessa wide variety of broadcast, streaming or stored content, such as localradio, satellite radio, streaming radio, stored music, podcasts,audiobooks, voice messages, instant messages or email. Yet having accessto so many content options from different sources can make it difficultfor users in a vehicle to access preferred content choices. For example,some content may be easily accessible using a vehicle's controls or byusing voice commands, while accessing other content may requireadditional steps using the vehicle's controls or using applications onan external user device. Such difficulties are compounded if a userwants to consume different types of content sequentially or create aplaylist from different content sources. This presents challenges forusers who want to control their consumption of content in a vehicle,particularly when driving. This can further lead to more instances ofdistracted driving.

Conventional entertainment systems such as described in U.S. Pat. No.10,108 619B2, CN104813680A, U.S. Pat. No. 10,067,988B2, US20140188920A1,and U.S. Pat. No. 9,088,572B2 describe standard playlists and coarseclassification of content. However, these systems do not contemplate letalone address the nuances associated with focus of driver attention,ever-changing context of driver, vehicle and extrinsic factors thataffect what is most important or relevant to a driver or passenger.Moreover, privacy implications and multi-modal factors as well as amulti-passenger environment with different user preferences and contextare not addressed by the state of the art.

SUMMARY

The following presents a summary to provide a basic understanding of oneor more embodiments of the invention. This summary is not intended toidentify key or critical elements or delineate any scope of thedifferent embodiments or any scope of the claims. Its sole purpose is topresent concepts in a simplified form as a prelude to the more detaileddescription that is presented later. In one or more embodimentsdescribed herein, systems, computer-implemented methods, apparatusand/or computer program products are presented that facilitate dynamicplaylist priority in a vehicle based upon user preferences and context.

According to one or more embodiments, a system comprises techniques thatfacilitate dynamic playlist priority in a vehicle based upon userpreferences and context that are prioritized in real time. The systemcan comprise a processor that executes computer executable componentsstored in at least one memory, a compilation component that receivescontent in a vehicle, an assessment component that respectivelyclassifies subsets of the content, a ranking component that ranksrelevancy of the classified subsets of content based upon preferencesand context of a user in the vehicle, a content playback component thatplays the subsets of classified content based upon relevancy ranking, aprioritization component that dynamically prioritizes a first subset ofthe content based upon the context of the user or context of a sender ofthe first subset of content, wherein the first subset of contentcomprises extrinsic data, and an interrupt component that interruptsplayback of the subsets of classified content based upon the dynamicprioritization.

In some embodiments, elements described in connection with the disclosedsystems can be embodied in different forms such as acomputer-implemented method, a computer program product, or anotherform.

DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example, non-limiting systemthat facilitates dynamic playlist priority in a vehicle based upon userpreferences and context in accordance with one or more embodimentsdescribed herein.

FIG. 2 illustrates a block diagram of another example, non-limitingsystem that facilitates dynamic playlist priority in a vehicle basedupon user preferences and context in accordance with one or moreembodiments described herein.

FIG. 3 illustrates a block diagram of another example, non-limitingsystem that facilitates dynamic playlist priority in a vehicle basedupon user preferences and context in accordance with one or moreembodiments described herein.

FIG. 4 illustrates yet another example of a non-limiting system thatfacilitates dynamic playlist priority in a vehicle and transfers theplayback of the subsets of classified content from a first device to asecond device in accordance with one or more embodiments describedherein.

FIG. 5 illustrates yet another example of a non-limiting system thatfacilitates dynamic playlist priority in a vehicle based uponpreferences and context of two or more individuals in the vehicle inaccordance with one or more embodiments described herein.

FIG. 6 illustrates yet another example of control component that enablesa user to selectively modify preferences with respect to a specificplaylist in accordance with one or more embodiments described herein.

FIG. 7 illustrates yet another example of a visualization component thatdisplays, summarizes and organizes a playlist in accordance with one ormore embodiments described herein.

FIG. 8 illustrates a flow diagram of an example of a method tofacilitate dynamic playlist priority in a vehicle in accordance with oneor more embodiments described herein.

DETAILED DESCRIPTION

The following detailed description is merely illustrative and is notintended to limit embodiments and/or application or uses of embodiments.Furthermore, there is no intention to be bound by any expressed orimplied information presented in the preceding Summary section or in theDetailed Description section.

Embodiments described herein include systems, methods, and computerprogram products that facilitate dynamic playlist priority in a vehiclebased upon user preferences and context. In many instances, the abilityto access a playlist that prioritizes and plays content for users in avehicle will significantly reduce the need to search for and selectcontent using a vehicle's controls or applications on an external userdevice, which reduces distracted driving. Also, by pushing content to auser through a playlist based upon the user's preferences and context,the user will have the opportunity to consume preferred content that theuser may have otherwise missed had the user been required to search forand select the content using a vehicle's controls or applications on anexternal user device.

One or more embodiments are now described with reference to thedrawings, wherein like referenced numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea more thorough understanding of the one or more embodiments. It isevident, however, in various cases, that the one or more embodiments canbe practiced without these specific details.

Turning now to the drawings, FIG. 1 illustrates a block diagram of anexample, non-limiting system 100 that facilitates dynamic playlistpriority in a vehicle based upon user preferences and context inaccordance with one or more embodiments described herein. The systemincludes a processor 102 that executes computer executable componentsstored in at least one memory 104. The system 100 can further include asystem bus 106 that can couple various components, including, but notlimited to, a compilation component 108, an assessment component 110, aranking component 112, a content playback component 114, aprioritization component 116 and an interrupt component 118. Thecompilation component 108 receives content in a vehicle. The assessmentcomponent 110 assesses and respectively classifies subsets of thecontent. The ranking component 112 ranks relevancy of classified subsetsof content based upon preferences and context of a user in the vehicle.The content playback component 114 plays the subsets of classifiedcontent as a playlist in an order based upon relevancy rankingdetermined by the ranking component 112. The prioritization component116 dynamically prioritizes a first subset of the content based uponcontext of the user or context of a sender of the first subset ofcontent, wherein the first subset of content comprises extrinsic data.For example, such extrinsic data can include: an email, an instantmessage, news alert, phone call, weather alert, traffic alert, proximityalert, government emergency alert, Amber alert, construction alert,social network alert, or the like. The interrupt component 118interrupts playback of the subsets of classified content based upon thedynamic prioritization.

In certain embodiments, the memory 104 used to store content received bythe compilation component 110 can be contained in at least one of avehicle, a cloud computing system or an external user device.

In certain embodiments, the compilation component 108 can receivecontent such as audio files or content convertible into audio filesalong with metadata relating to the content. Such content and relatedmetadata can be received from one or more broadcast, streaming or storedcontent sources, such as local radio, satellite radio, streaming radio,music stored on an external user device, podcasts, audiobooks, voicemessages, instant messages or email. Metadata can include a wide varietyof information relating to a particular content file, portions of acontent file or sets and subsets of related content files. One exampleincludes descriptive metadata such as an abstract, a title or subtitle,keywords or hashtags taken directly from the content source, or usercomments or ratings from a source such as a social media platform.Another example can include transcript(s) of certain audio files such asfor example news reports. With respect to music, examples can includegenre, song title, artist, album, songwriter and release date.

In certain embodiments, the compilation component 108 records and storesbroadcast or streaming content based upon preferences of a user. Forexample, a user may want all content produced by a particular talk showover the past week or other time period available for possible inclusionin a playlist. A user may also desire all segments from a variety ofshows or other content sources that relate to a specific topic orinclude certain individuals be available for possible inclusion in aplaylist.

In certain embodiments, the assessment component 110 can classifysubsets of the content and related metadata received by the compilationcomponent 108 based upon a variety of attributes. Certain attributes canbe broadly defined, such as music versus talk radio or podcasts andsports versus politics. Others can be more narrowly defined such aspolitical news versus political opinion or debate or even more specificcategories such as political perspective. For example, in the sportsgenre, relevant attributes can include items such as type of sport,team, city, state, region, country, conference, players and coaches.Other attributes can include shows or individuals who provide sportsanalysis and opinion. The assessment component 110 can utilize a varietyof methods to classify the subsets of content. For example, arules-based classification system can rely first on title, subtitles anddescriptive metadata with respect to certain content, such as a “healthcare debate” or “World Cup predictions,” but absent such titles,subtitles or descriptive metadata can then rely upon machine learningtechnology to identify specific content attributes such as subjectmatter based upon the transcript for such content or comments related tosuch content in social media.

In another example, the assessment component 110 can be customized toenable a user to selectively modify or create one or more attributesused to classify one or more categories of content. For example, a usermay prefer a particular talk show, but only with respect to one or moreregular segments of that show. Another user may prefer that talk show,but only when a particular guest is on the show or a particular topic isbeing discussed. Because two users may want to assign differentattributes when classifying content such as a talk show, the assessmentcomponent 110 can be modified depending on the preferences of the userusing the dynamic playlist priority system 106. This enables a user tocreate attributes tailored to that user that enable the assessmentcomponent 110 to better assess and categorize content in a manner besttailored to the preferences of that user.

In certain embodiments, the ranking component 112 can rank relevancy ofthe subsets of content classified by the assessment component 110 basedupon preferences and context of a user in the vehicle. In one example, auser can rank or exclude content based upon one or more attributesutilized by the assessment component 110 to classify content. Rankingscan also be dependent on one or more attributes. For example, a user mayonly want to consume news content from a particular network if one ormore anchors, analysts or guests ranked highly by the user are includedin a particular content segment.

In another example, the ranking component 112 can determine preferencesof a user through a questionnaire to be completed by the user andthrough subsequent questionnaires at time intervals that can be selectedby the user. Questionnaires can be used to determine a user'spreferences to various types of content and how such user preferenceswill vary depending on context. The ranking component 112 can alsoenable a user to indicate or modify preferences at any time. Forexample, a user may decide to express a stronger preference for certaintypes of content in anticipation of upcoming events such as playoffs ina particular sport or political elections. A user may also decide toexpress less of a preference for certain types of content after losinginterest in one or more items in a recent playlist.

In another example, a user can select how the user's content preferenceswill vary based upon context. A user may decide that on the user's dailycommute to work that the ranking component 112 will rank news, sportsand important work-related emails over other content types, while on theuser's commute home from work the ranking component 112 will rank afavorite podcast and instant messages from family and friends over othercontent types. For daily driving around town the user may instruct theranking component 112 to rank certain music genres and all instantmessages higher while longer trips entered into the vehicle's navigationsystem will cause the ranking component 112 to rank a certain audiobookand instant messages from select senders higher. In another example, auser's preferences with respect to certain content may vary depending onthe time of year. A user many decide that content relating to a specificsport should be excluded from playlists in the offseason unless itinvolves breaking news for the local team, should be included inplaylists during the season and should be given the highest rankingduring the postseason. In another example, a user can indicate apreference against any news or commentary regarding political electionsuntil three months prior to and one week following an election.

In certain embodiments, the content playback component 114 plays thesubsets of classified content based upon the relevancy ranking generatedby the ranking component 112. The content playback component 114 canplay content utilizing the speaker system of a vehicle or an externaluser device. In one example, with respect to content received by thecompilation component 108 as text files as opposed to audio files, theplayback component 114 will utilize a text to speech component to playthe content.

In certain embodiments, the prioritization component 116 can dynamicallyprioritizes a first subset of the content based upon the context of theuser or context of a sender of the first subset of content, wherein thefirst subset of content comprises extrinsic data. For example, suchextrinsic data can include an email, an instant message, news alert,phone call, weather alert, traffic alert or proximity alert, governmentemergency alert, Amber alert, construction alert, social network alert,or the like.

Once the ranking component 112 creates a playlist for a user in avehicle, the prioritization component 116 can alter the playlist in realtime based upon the context of the situation. For example, a user canidentify the types of situations that might alter the user's preferencesin real time. In one example, a user can specify in circumstances ofintense weather that the prioritization component 116 will prioritizelocal weather reports from a specific source and in circumstances ofhigh traffic that the prioritization component will prioritize trafficreports and alternate routes from all available sources.

In another example, the context of the sender of content can cause theprioritization component 116 to alter the playlist. For example, a usermay prefer to have certain work-related emails and instant messages fromcolleagues and clients read to the user during the user's drive to workin the morning but not on the way home. Also, the user may prefer to nothave instant messages from family and friends read to the user duringthe user's drive to work in the morning but prefers to hear them on theway home. But these preferences can be altered based upon the context ofthe sender. If a user's spouse is traveling out of town, a user mayprefer that any emails or texts sent by the spouse while out of town beprioritized regardless of when sent. Similar examples can include afriend of colleague recovering from an illness in a hospital or a sickchild at home instead of at school.

In certain embodiments, the interrupt component 118 interrupts playbackof the subsets of classified content based on the dynamic prioritizationby the prioritization component 116. While the prioritization component116 will dynamically prioritize a content playlist in real time, a usercan indicate preferences regarding types of content associated withextrinsic data that warrant interrupting the playlist as opposed tobeing included in the playlist after other content is played. Forexample, a user may decide that an instant message or email from aspouse who is traveling should be prioritized by the prioritizationcomponent 116 and thus included in a playlist in real time, but the usermay also decide that a phone call, instant message or email from aspouse that originates from a hospital should result in an interruptionby the interrupt component 118. In another example, a user may decidethat an email from a colleague or client marked important should beprioritized by the prioritization component 116 and thus included in aplaylist in real time, but the user may also decide that an email from acolleague or client marked important on a day that a meeting isscheduled with that colleague or client should result in an interruptionby the interrupt component 118. In another example, a user can indicatea preference that if a spouse, child, colleague or client makes at leastthree attempts to reach a user through a phone call, instant message oremail within a short period of time, thus indicating a potentiallyimportant message, interrupt component 118 should interrupt a playlist.In another example, a user can indicate a preference that a weatheralert should result in an interruption by the interrupt component 118only during winter month or if the extrinsic data is associated with aweather emergency. In another example, a user can indicate a preferencethat a proximity alert for a gas station should result in aninterruption by the interrupt component 118 only when the available fuellevel in the vehicle is below a specified level.

In another example, the interrupt component 118 provides different typesof interruption based on a user's preference. A user can choose to havecertain content associated with extrinsic data identified by theprioritization component 116 immediately played in full, while othercontent associated with extrinsic data identified by the prioritizationcomponent 116 will only generate an alert that important content hasbeen received and can be accessed and played in full at the option ofthe user. For example, a user may prefer that any content from theuser's spouse or children identified by the prioritization component 116should be immediately accessed in full by the interrupt component 118,while any content from the user's colleagues or clients identified bythe prioritization component 116 should only generate an alert by theinterrupt component 118 that important content has been received and canbe accessed.

FIG. 2 illustrates a block diagram of another example, non-limitingsystem that facilitates dynamic playlist priority in a vehicle basedupon user preferences and context in accordance with one or moreembodiments described herein. Repetitive description of like elementsemployed in respective embodiments is omitted for sake of brevity. Incertain embodiments, the system 200 includes control component 202 thatenables a user to select specific content or create customized rankingswith respect to the planned use of a vehicle for a specified timeperiod. For example, a user planning a long drive may select a series ofpodcasts for that trip. In the aftermath of a significant news story, auser can indicate a preference to only hear news reports and commentaryregarding that news story for the next day. This control component canthus be used to tailor playlists to the preferences of a user withrespect to a particular situation. In another example, the controlcomponent 202 can be utilized using a vehicle's controls or through useof an external user device. For example, a user can skip content or makecontent selections from a playlist using controls on the center stack ofa dashboard or on the steering wheel or by using a vehicle'svoice-enabled controls.

FIG. 3 illustrates a block diagram of another example, non-limitingsystem that facilitates dynamic playlist priority in a vehicle basedupon user preferences and context in accordance with one or moreembodiments described herein. In certain embodiments, the system 300includes visualization component 302 that displays, summarizes andorganizes a playlist in accordance with one or more embodimentsdescribed herein. In one example, the visualization component canconsist of a touchscreen in the center stack of a vehicle that displaysa graphical user interface (GUI) comprising touch controls to controlfunctions of the vehicle. The visualization component 302 can provide avariety of screen displays available to a user depending how muchinformation regarding a playlist and related metadata a user selects tohave displayed. For example, the visualization component 302 can displaydetailed information regarding the content item currently being playedby the content playback component 114 along with the title of nextcontent item on the playlist, or the visualization component can listthe currently played content item and some number of upcoming contentitems on the playlist in order to provide a user more control regardingskipping past playlist content items. In another example, the manner inwhich playlists and related metadata are displayed can depend on thetype of content included in a playlist or the context. For example, auser can specify that any playlists including music or items such asemails or instant messages be listed with detailed metadata in a listformat displaying upcoming content items. Also, for safety reasons, suchlisting displays can revert to only displaying the content itemcurrently being played by the content playback component 114 along withthe title of next content item on the playlist whenever the vehicle istraveling above a certain speed in order to cause less distraction forthe driver. In another example, a playlist and related metadata can bedisplayed as one of the options on a windshield display immediately infront of the driver or on an external user device used by a passenger inthe vehicle.

In certain embodiments, the system 300 includes multi-modal component304 that transfers playback of the subsets of classified content from afirst device to a second device in accordance with one or moreembodiments described herein.

In certain embodiments, the system 300 includes machine learningcomponent 306 enabling the ranking component 112 or prioritizationcomponent 116 to utilize artificial intelligence and machine learning tolearn the behavior of a user with respect to playback of content invarious contexts, and update the relevancy ranking generated by theranking component 112 and the dynamic prioritization generated by theprioritization component 116 based upon the learned user behavior. Forexample, a user may consistently skip work email from several colleagueson the way to work even after expressing a preference to receive workemails on the user's daily commute to work. In another example, a usermay consistently skip news programs regarding a specific story eventhough the general topic is preferred by the users. This and otherbehavior by a user can be used by the machine learning component 306 tomodify and improve the relevancy of playlists generated by the rankingcomponent 112 and the dynamic prioritization generated by theprioritization component 116 depending on the context. In anotherexample, user behavior can be used by the machine learning component 306to supplement or modify questions in subsequent questionnaires used totrain the ranking component 112 and the prioritization component 116 inorder confirm or adjust new relevancy rankings generated by the rankingcomponent 112 or dynamic prioritizations generated by the prioritizationcomponent 116.

In another example, the machine learning component 306 can train theassessment component 110 to identify certain attributes used to classifycontent utilizing information provided by users of the system 300 whocreate or modify attributes used to classify one or more categories ofcontent. For example, as more users select a particular attribute suchas segment or guest to classify a talk show, the system 300 can applythose attributes more broadly to enable other users to indicate similarpreferences. In another example, as new topics emerge in genres such asentertainment, politics and sports, the machine learning component 306can train the assessment component 110 to identify such additionaltopics in the content and related metadata received by the compilationcomponent 108 and create applicable attributes that can be used toclassify such content.

In this regard, the machine learning component 306 can performclassifications, correlations, inferences and/or expressions associatedwith principles of artificial intelligence. For instance, the machinelearning component 306 can employ an automatic classification systemand/or an automatic classification. In one example, the machine learningcomponent 306 can employ a probabilistic and/or statistical-basedanalysis (e.g., factoring into the analysis utilities and costs) tolearn and/or generate inferences. The machine learning component 306 canemploy any suitable machine-learning based techniques, statistical-basedtechniques and/or probabilistic-based techniques. For example, themachine learning component 306 can employ expert systems, fuzzy logic,SVMs, Hidden Markov Models (HMMs), greedy search algorithms, rule-basedsystems, Bayesian models (e.g., Bayesian networks), neural networks,other non-linear training techniques, data fusion, utility-basedanalytical systems, systems employing Bayesian models, etc. In anotheraspect, the machine learning component 306 can perform a set of machinelearning computations. For example, the machine learning component 306can perform a set of clustering machine learning computations, a set oflogistic regression machine learning computations, a set of decisiontree machine learning computations, a set of random forest machinelearning computations, a set of regression tree machine learningcomputations, a set of least square machine learning computations, a setof instance-based machine learning computations, a set of regressionmachine learning computations, a set of support vector regressionmachine learning computations, a set of k-means machine learningcomputations, a set of spectral clustering machine learningcomputations, a set of rule learning machine learning computations, aset of Bayesian machine learning computations, a set of deep Boltzmannmachine computations, a set of deep belief network computations, and/ora set of different machine learning computations. FIG. 4 illustrates yetanother example of a non-limiting system that facilitates dynamicplaylist priority in a vehicle and further comprises a multi-modalcomponent that transfers playback of the subsets of classified contentfrom a first device 402 to a second device 404 in accordance with one ormore embodiments described herein. FIG.4 depicts a view of the interiorof a vehicle with a driver seated in the driver's seat and holding asmartphone 404. In this example, the playlist generated by the rankingcomponent 112 in the vehicle that has been playing utilizing the contentplayback component 114 in the vehicle 402 is being transferred utilizingthe multi-model component 304 to an application on the driver'ssmartphone 404 through which playback of the playlist can continue asdriver exits the vehicle. In another example, the multi-modal component304 transfers the playback of the subsets of classified content from afirst device 402 to other external user devices. In one example, a usercan elect to transfer the playback of a playlist to a smartphone 404 orother external user device before exiting the vehicle. A user can alsoelect to save the playlist in the cloud to access and play at anothertime. In another example, a user can select certain playlists, types ofplaylists or parts pf playlists that will automatically transfer to anexternal user device or the cloud. For example, a user may only wantcontent related to music or news transferred to an external user deviceif the user elects to transfer such content as he is leaving a vehicle.In another example, a user may want all content in a playlist related tosports talk saved in the cloud to be accessed later at the user'sdiscretion.

In another example, the multi-modal component 304 can enable a user'spreferences to be transferred to another vehicle used by the user forplaylist playback. Such other vehicle can access user's preferences bysyncing with one of the user's external user devices or by enablingaccess to the user's preferences stored in the cloud.

FIG. 5 illustrates yet another example of a non-limiting system thatfacilitates dynamic playlist priority in a vehicle based uponpreferences and context of two or more individuals in the vehicle inaccordance with one or more embodiments described herein. In thisexample, the ranking component 112 ranks the relevancy of the classifiedsubsets of content based upon preferences and context of two or moreindividuals in the vehicle. FIG.5 depicts a view of the interior ofvehicle with three people, including a driver 502 seated in the driver'sseat, a first passenger 504 seated in the front passenger seat, and asecond passenger 506 seated in a back seat of the vehicle behind thedriver. In one example, the driver's playlist generated by the rankingcomponent 112 is modified due to the presence of at least one passengerto remove all podcasts and audiobooks from the playlist. The vehicle candetect presence of other passengers using sensors and syncing with anyexternal user devices that can identify individuals, and the rankingcomponent 112 can also prompt the driver to confirm the presence andidentity of other passengers. In one example, if a first passenger 504is the driver's spouse and the second passenger 506 is the driver's son,the driver's playlist will exclude all emails and instant messages basedon the preferences of the driver 502. In another example, if only thedriver's spouse is in the vehicle as the first passenger 504, thedriver's playlist will exclude all emails and instant messages andinclude news and music based on the preferences of the driver 502. Inanother example, if only the driver's son is in the vehicle as the firstpassenger 504, the driver's playlist will exclude all emails and instantmessages and include sports and music based on the preferences of thedriver 502. In another example, if the other passengers are individualsother that a user's family but are not identified by the rankingcomponent, the driver's playlist will only include music based on thepreferences of the driver 502. In another example, a privacy mode can beenabled when one or more additional passengers are in the vehiclecausing all emails, instant messages and voice messages, or emails,instant messages and voice messages from certain senders or groups ofsenders, to be excluded from playlists or interruptions, or enabling auser to see emails, instant messages and voice messages included in aplaylist by the ranking component 112 or the prioritization component116 using the visualization component 118 so that the user can decidewhether to have one or more of such emails, instant messages or voicemessages played in the presence of the passengers.

In another example, user profiles can be created for frequent passengersin a primary user's vehicle such as family members, friends andcolleagues and clients. This enables a user to further tailor the user'scontent preferences depending on the identify of more passengers. Forexample, a user may have friends that share a passion for a particularsport or activity and can thus indicate preferences that only contentconsisting of news, talk shows or podcasts relating to that sport oractivity be included in playlists when one or more of those friends arepassengers.

In another example, the preferences of at least one other passenger canbe taken into account in generating a playlist to be played by thecontent playback component 114. In this example, the ranking component112 generates a combined relevancy ranking based on the combinedpreferences a first and second user in the vehicle. In one example, if afirst passenger 504 is the driver's spouse and the second passenger 506is the driver's son, the driver's playlist will exclude all emails andinstant messages based on the preferences of the driver 502, and theplaylist generated from all content not excluded will take into accountthe preferences of each of the driver 502, the first passenger 504 andthe second passenger 506. In this example, the ranking component 122 maygenerate a playlist based solely on news, talk shows or podcastsrelating to a particular sport due to the varied preferences of thethree passengers. In another example, if only the driver's spouse is inthe vehicle as the first passenger 504, the ranking component 122 maygenerate a playlist that includes news and music in genres that bestmatch the preferences of both the driver 502 and the first passenger504.

In another example, utilizing the multi-model component 304, the contentplayback component 114 can generate and respectively play personalizedstreams of ranked content to a first user and a second user onrespective playback devices based up rankings generated by the rankingcomponent 112 with respect to each user. In one example, if a firstpassenger 504 is the driver's spouse and the second passenger 506 is thedriver's son, and the first passenger elects to receive content throughan external user device 510, then a playlist can be tailored to thefirst passenger's preferences by the ranking component 112, and thefirst passenger 504 can receive that playlist from the content playbackcomponent 114 sent to the external user device 510. In this example, anyplaylist generated ranking component 112 for the driver 502 and thesecond passenger 506 will not take into account the presence of thefirst passenger 504 when generating such playlist, and such playlistwill be played by the content playback component 114 using the vehicle'scontent delivery system 508. If the second passenger 504 stops playingor turns off the external user device 510, the content playbackcomponent 114 can modify the playlist being played using the vehicle'scontent delivery system 508 to take into account the presence of thesecond passenger 504.

FIG. 6 illustrates yet another example of a control component 202 thatenables a user to selectively modify preferences with respect to aspecific playlist in accordance with one or more embodiments describedherein. FIG.6 depicts a view of the steering wheel and the center stackof the interior dashboard of vehicle with controls available to a useron the steering wheel 602, the vehicle touchscreen 604 that displays aGUI comprising touch controls and additional controls on the centerstack 606 to control functions of the vehicle. In one example, a usercan use one or more of the controls on the steering wheel 602, thevehicle touchscreen 604 or the center stack 606 to skip one or morecontent items in a playlist as the playlist is being played or return toprevious content items previously played in the playlist.

In another example a user can use voice commands in a vehicle thatenables voice controls to skip one or more content items in a playlistas the playlist is being played or return to previous content itemspreviously played in the playlist. In another example, a user can usevoice commands in a vehicle that enables voice controls to search aplaylist for a specific topic or content type. For example, a user cansearch for any content in a playlist relating to a game or news eventfrom the previous evening.

FIG. 7 illustrates yet another example of a visualization component 302that displays, summarizes and organizes a playlist in accordance withone or more embodiments described herein. FIG. 7 depicts an example of avisualization component 302 in the form of an enlarged view of anexample GUI displayed on a vehicle touchscreen that can reside in thecenter stack of the dashboard of a vehicle. In this example, thetouchscreen displays the upcoming items of a playlist generated by theranking component 112. The items are displayed by topic, with the firstitem being “Sports News” 704, the next item being “Talk Radio—Politics”706, the next item being “Work Emails” 708, and the last item being“Music—Classic Rock” 710. This enables a user to see upcoming items andselect an item the user desired to listen to first. In this example theuser 712 selects the second item listed 706. In another example, thevisualization component 302 can provide a variety of GUI configurationsto display the items on a playlist and related metadata to enable userto skip items or select items in a playlist that best match a user'spreferences in that moment. For example, some users may want to seecontent items in a playlist displayed by topic as shown in FIG. 7, whileother users may prefer more detailed information regarding the contentitems such as specific participants and content titles. In anotherexample, a user may want to have all content items in a playlistdisplayed on a touchscreen with a scrolling function in the GUI thatenables the user to browse all items.

In another embodiment, with respect to a playlist personalized anddelivered to an external user device for an individual user in a vehicleutilizing the multi-modal component 304, the visualization component 302can comprise an augmented reality component or virtual reality componentto display playlist information for such user and enable the user tomake playlist decisions such as skipping or selection content items. Inone example, a user using an augmented reality headset for bettervisualization of peripheral and rear views while driving can haveplaylist information visualized using the augmented reality headset in amanner that doesn't interfere with driving functions. In anotherexample, a passenger listening to a personalized playlist while wearingan augmented reality or virtual reality headset to learn about or betterenjoy the surroundings during a drive can have playlist informationvisualized using the augmented reality or virtual reality headset.

FIG. 8 illustrates a flow diagram of an example of a method tofacilitate dynamic playlist priority in a vehicle in accordance with oneor more embodiments described herein. Act 802 represents a first actwhich includes receiving content in a vehicle. At 804, subsets of thecontent are classified. At 806, relevancy of the classified subsets ofcontent are ranked based upon preferences and context of a user in thevehicle. At 808, the subsets of classified content are played based uponthe relevancy ranking. At 810, a first subset of the content isdynamically prioritized based upon the context of the user or context ofa sender of the first subset of content, wherein the first subset ofcontent comprises extrinsic data. At 812, playback of the subsets ofclassified content is interrupted based on the dynamic prioritization.

The one or more embodiments of the present invention may be a system, amethod, an apparatus and/or a computer program product at any possibletechnical detail level of integration. The computer program product caninclude a computer readable storage medium (or media) having computerreadable program instructions thereon for causing a processor to carryout aspects of the present invention. The computer readable storagemedium can be a tangible device that can retain and store instructionsfor use by an instruction execution device. The computer readablestorage medium can be, for example, but is not limited to, an electronicstorage device, a magnetic storage device, an optical storage device, anelectromagnetic storage device, a semiconductor storage device, or anysuitable combination of the foregoing. A non-exhaustive list of morespecific examples of the computer readable storage medium can alsoinclude the following: a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), a static randomaccess memory (SRAM), a portable compact disc read-only memory (CD-ROM),a digital versatile disk (DVD), a memory stick, a floppy disk, amechanically encoded device such as punch-cards or raised structures ina groove having instructions recorded thereon, and any suitablecombination of the foregoing. A computer readable storage medium, asused herein, is not to be construed as being transitory signals per se,such as radio waves or other freely propagating electromagnetic waves,electromagnetic waves propagating through a waveguide or othertransmission media (e.g., light pulses passing through a fiber-opticcable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. Computer readable programinstructions for carrying out operations of the present invention can beassembler instructions, instruction-set-architecture (ISA) instructions,machine instructions, machine dependent instructions, microcode,firmware instructions, state-setting data, configuration data forintegrated circuitry, or either source code or object code written inany combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) can execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects of the present invention.

Various aspects of the present invention are described herein withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems), and computer program products according toembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer readable program instructions. These computerreadable program instructions can be provided to a processor of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionscan also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks. The computer readable program instructions can also be loadedonto a computer, other programmable data processing apparatus, or otherdevice to cause a series of operational acts to be performed on thecomputer, other programmable apparatus or other device to produce acomputer implemented process, such that the instructions which executeon the computer, other programmable apparatus, or other device implementthe functions/acts specified in the flowchart and/or block diagram blockor blocks.

The flowcharts and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams can represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks can occur out of theorder noted in the Figures. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While the subject matter has been described above in the general contextof computer-executable instructions of a computer program product thatruns on a computer and/or computers, those skilled in the art willrecognize that this disclosure also can or can be implemented incombination with other program modules. The illustrated aspects can alsobe practiced in distributed computing environments in which tasks areperformed by remote processing devices that are linked through acommunications network. However, some, if not all aspects of thisdisclosure can be practiced on stand-alone computers. In a distributedcomputing environment, program modules can be located in both local andremote memory storage devices.

As used in this application, the terms “component,” “system,”“platform,” “interface,” and the like, can refer to and/or can include acomputer-related entity or an entity related to an operational machinewith one or more specific functionalities. The entities disclosed hereincan be either hardware, a combination of hardware and software,software, or software in execution. For example, a component can be, butis not limited to being, a process running on a processor, a processor,an object, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running on aserver and the server can be a component. One or more components canreside within a process and/or thread of execution and a component canbe localized on one computer and/or distributed between two or morecomputers. In another example, respective components can execute fromvarious computer readable media having various data structures storedthereon. The components can communicate via local and/or remoteprocesses such as in accordance with a signal having one or more datapackets (e.g., data from one component interacting with anothercomponent in a local system, distributed system, and/or across a networksuch as the Internet with other systems via the signal). As anotherexample, a component can be an apparatus with specific functionalityprovided by mechanical parts operated by electric or electroniccircuitry, which is operated by a software or firmware applicationexecuted by a processor. In such a case, the processor can be internalor external to the apparatus and can execute at least a part of thesoftware or firmware application. As yet another example, a componentcan be an apparatus that provides specific functionality throughelectronic components without mechanical parts, wherein the electroniccomponents can include a processor or other means to execute software orfirmware that confers at least in part the functionality of theelectronic components. In an aspect, a component can emulate anelectronic component via a virtual machine, e.g., within a cloudcomputing system.

As it is employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Further, processors can exploit nano-scalearchitectures such as, but not limited to, molecular and quantum-dotbased transistors, switches and gates, in order to optimize space usageor enhance performance of user equipment. A processor can also beimplemented as a combination of computing processing units. In thisdisclosure, terms such as “store,” “storage,” “data store,” datastorage,” “database,” and substantially any other information storagecomponent relevant to operation and functionality of a component areutilized to refer to “memory components,” entities embodied in a“memory,” or components comprising a memory. It is to be appreciatedthat memory and/or memory components described herein can be eithervolatile memory or nonvolatile memory, or can include both volatile andnonvolatile memory. Additionally, the disclosed memory components ofsystems or computer-implemented methods herein are intended to include,without being limited to including, these and any other suitable typesof memory.

What has been described above include mere examples of systems andcomputer-implemented methods. It is, of course, not possible to describeevery conceivable combination of components or computer-implementedmethods for purposes of describing one or more embodiments, but one ofordinary skill in the art can recognize that many further combinationsand permutations of these embodiments are possible. The descriptions ofthe various embodiments have been presented for purposes ofillustration, but are not intended to be exhaustive or limited to theembodiments disclosed. Many modifications and variations will beapparent to those of ordinary skill in the art without departing fromthe scope and spirit of the described embodiments.

Furthermore, to the extent that the terms “includes,” “has,”“possesses,” and the like are used in the detailed description, claims,appendices and drawings such terms are intended to be inclusive in amanner similar to the term “comprising” as “comprising” is interpretedwhen employed as a transitional word in a claim. The terminology usedherein was chosen to best explain the principles of the embodiments, thepractical application or technical improvement over technologies foundin the marketplace, or to enable others of ordinary skill in the art tounderstand the embodiments disclosed herein. In addition, the term “or”is intended to mean an inclusive “or” rather than an exclusive “or.”That is, unless specified otherwise, or clear from context, “X employs Aor B” is intended to mean any of the natural inclusive permutations.That is, if X employs A; X employs B; or X employs both A and B, then “Xemploys A or B” is satisfied under any of the foregoing instances.Moreover, articles “a” and “an” as used in the subject specification andannexed drawings should generally be construed to mean “one or more”unless specified otherwise or clear from context to be directed to asingular form. As used herein, the terms “example” and/or “exemplary”are utilized to mean serving as an example, instance, or illustration.For the avoidance of doubt, the subject matter disclosed herein is notlimited by such examples. In addition, any aspect or design describedherein as an “example” and/or “exemplary” is not necessarily to beconstrued as preferred or advantageous over other aspects or designs,nor is it meant to preclude equivalent exemplary structures andtechniques known to those of ordinary skill in the art.

What is claimed is:
 1. A system, comprising: a processor that executescomputer executable components stored in at least one memory; acompilation component that receives content in a vehicle; an assessmentcomponent that respectively classifies subsets of the content; a rankingcomponent that ranks relevancy of the classified subsets of contentbased upon preferences and context of a user in the vehicle; a contentplayback component that plays the subsets of classified content basedupon relevancy ranking; a prioritization component that dynamicallyprioritizes a first subset of the content based upon the context of theuser or context of a sender of the first subset of content, wherein thefirst subset of content comprises extrinsic data; and an interruptcomponent interrupts playback of the subsets of classified content basedon the dynamic prioritization.
 2. The system of claim 1, furthercomprising a multi-modal component that transfers the playback of thesubsets of classified content from a first device to a second device. 3.The system of claim 1, wherein the ranking component ranks relevancy ofthe classified subsets of content based upon preferences and context oftwo or more individuals in the vehicle.
 4. The system of claim 3,wherein the content playback component includes a multiplexing componentthat generates and respectively plays personalized streams of rankedcontent to a first user and a second user on respective playbackdevices.
 5. The system of claim 1, wherein the ranking componentutilizes the extrinsic data to rank relevancy of the classified subsetsof content.
 6. The system of claim 1, further comprising a controlcomponent that enables a user to selectively modify preferences withrespect to a specific playlist.
 7. The system of claim 1, furthercomprising an artificial intelligence or machine learning component thatlearns behavior of the user with respect to playback of the subsets ofclassified content, and updates relevancy ranking based upon the learneduser behavior.
 8. The system of claim 1, further comprising avisualization component that displays, summarizes and organizes aplaylist.
 9. The system of claim 8, wherein the visualization componentcomprises an augmented reality component or virtual reality component.10. The system of claim 5, wherein the content playback component thatplays the subsets of classified content based upon a combined relevancyranking of the first and second user.
 11. A computer-implemented method,comprising employing a processor to execute computer executablecomponents stored in at least one memory to perform the following acts:receiving content in a vehicle; classifying subsets of the content;ranking relevancy of the classified subsets of content based uponpreferences and context of a user in the vehicle; playing the subsets ofclassified content based upon the relevancy ranking; dynamicallyprioritizing a first subset of the content based upon the context of theuser or context of a sender of the first subset of content, wherein thefirst subset of content comprises extrinsic data; and interruptingplayback of the subsets of classified content based on the dynamicprioritization.
 12. The method of claim 11, further comprisingtransferring the playback of the subsets of classified content from afirst device to a second device.
 13. The method of claim 11, furthercomprising ranking relevancy of the classified subsets of content basedupon preferences and context of two or more individuals in the vehicle.14. The method of claim 12, further comprising generating andrespectively playing personalized streams of ranked content to a firstuser and a second user on respective playback devices.
 15. The method ofclaim 11, further comprising utilizing extrinsic criteria to rankrelevancy of the classified subsets of content.
 16. The method of claim11, further comprising receiving from a user instructions to selectivelymodify preferences with respect to a specific playlist.
 17. The methodof claim 11, further comprising using an artificial intelligence ormachine learning component to learn behavior of the user with respect toplayback of the subsets of classified content, and updating relevancyranking based upon the learned user behavior.
 18. The method of claim11, further comprising displaying, summarizing and organizing aplaylist.
 19. The method of claim 11, further comprising presenting theclassified subsets of content in an augmented reality or virtual realityenvironment.
 20. The method of claim 14, further comprising playing thesubsets of classified content based upon a combined relevancy ranking ofthe first and second user.
 21. A computer program product comprising acomputer readable storage medium having program instructions embodiedtherewith, the program instructions executable by processor to cause theprocessor to: receiving content in a vehicle; classifying subsets of thecontent; ranking relevancy of the classified subsets of content basedupon preferences and context of a user in the vehicle; playing thesubsets of classified content based upon the relevancy ranking;dynamically prioritizing a first subset of the content based upon thecontext of the user or context of a sender of the first subset ofcontent, wherein the first subset of content comprises extrinsic data;and interrupting playback of the subsets of classified content based onthe dynamic prioritization.